The interferometric synthetic aperture radar (InSAR) technique is widely adopted for detecting and monitoring landslides, but its effectiveness is often degraded in mountainous terrains, due to geometric distortions in the synthetic aperture radar (SAR) image input. To evaluate the terrain effect on the applicability of InSAR in landslide monitoring, a variety of visibility evaluation models have been developed, among which the R-index models are quite popular. In consideration of the poor performance of the existing R-index models in the passive layover region, this study presents an improved R-index model, in which a coefficient for improving the visibility evaluation in the far passive layover regions is incorporated. To demonstrate the applicability of the improved R-index model, the terrain visibility of SAR images in Fengjie, a county in the Three Gorges Reservoirs region, China, is studied. The effectiveness of the improved R-index model is demonstrated through comparing the visibility evaluation results with those obtained from the existing R-index models and P-NG method. Further, the effects of the line-of-sight (LOS) parameters of SAR images and the resolution of the digital elevation model (DEM) on the terrain visibility are discussed.
Landslide is one of the most destructive geohazards around the world. The destruction of a landslide can be estimated from its deformation and runout behaviors, which might be simulated with numerical software such as particle flow code (PFC). In the PFC simulation of the runout behavior of a landslide, the results are dependent upon the particle‐particle contact micro‐parameters (e.g., contact modulus and friction coefficient). The calibration of the micro‐parameters of the PFC models is a challenge and various uncertainties are involved. The uncertainty in the selection of the modelling parameters leads to uncertainty in the simulated runout behavior of the landslide. As a result, the damage potential of the landslide cannot be accurately evaluated. To this end, this paper presents a probabilistic analysis of the runout behavior of the Jiweishan landslide, in which the uncertainty in the selection of the particle‐particle contact micro‐parameters is explicitly considered. Here, the input micro‐parameters are modeled as discrete random variables, the possible realizations of which are obtained through an orthogonal analysis of the PFC simulation‐based uniaxial compression tests. The derived possible realizations of the micro‐parameters are then adopted as the inputs to the built model of the landslide. With the results obtained from these PFC simulations, the runout behaviors of the Jiweishan landslide, such as the runout distance and the deposit thickness, are studied probabilistically. The results provide an improved estimate of the landslide runout behavior and further aid in making an informed risk assessment of the landslide.
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